Robustified Gaussian quasi-BIC for volatility

Shoichi Eguchi; Hiroki Masuda

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arXiv · 2603.29463

Robustified Gaussian quasi-BIC for volatility

Shoichi Eguchi·Hiroki Masuda

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Abstract

We develop a theoretical foundation for robust model comparison in a class of non-ergodic continuous volatility regression models contaminated by finite-activity jumps. Using the density-power weighting and the H\"{o}lder(-inequality)-based normalization of the conventional Gaussian quasi-likelihood function, we propose two Schwarz-type statistics and also establish their model selection consistency with respect to the minimal true parametric volatility coefficient. Numerical experiments are conducted to illustrate our theoretical findings.

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Shoichi Eguchi, Hiroki Masuda. 2026-03-31. Robustified Gaussian quasi-BIC for volatility. https://arxiv.org/abs/2603.29463

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